Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Total Active power [W] has constant value "0" Constant
Reactive power generator 0,Total accumulated [var] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Total reactive power [var] has constant value "0" Constant
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 3 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 9 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 8 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average ServiceOn Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h]High correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h] and 1 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Blades PitchAngle StdDev [°] and 3 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Blades PitchAngle Min. [°] and 5 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (58.3%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (51.9%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (53.2%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (54.5%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (78.2%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (73.6%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (72.8%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (76.7%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (74.1%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (87.3%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (58.3%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (67.0%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (72.7%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (65.1%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (65.5%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (62.4%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (61.4%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (53.9%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (50.9%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (56.4%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.2%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (86.4%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.0%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (69.2%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (79.5%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (83.7%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (69.8%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (58.9%) Imbalance
Grid RotorInvPhase2 Temp. Avg. [°C] is highly imbalanced (55.2%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (55.1%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (78.8%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (67.1%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.8%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.3%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.8%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.9%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (74.7%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (73.4%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (74.0%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (72.9%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (72.3%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (63.0%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (73.8%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (57.3%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (80.2%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (77.2%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (74.7%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (78.6%) Imbalance
Active power limit [W] is highly imbalanced (98.6%) Imbalance
Active power limit source is highly imbalanced (99.9%) Imbalance
Power factor set point is highly imbalanced (99.9%) Imbalance
Power factor set point source is highly imbalanced (99.9%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (90.2%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (59.3%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (74.8%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (58.4%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (81.7%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (70.4%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (55.5%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (54.2%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (57.8%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (74.1%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (74.9%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (79.3%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (50.7%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.7%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (99.0%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (98.7%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (97.0%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (80.8%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (59.5%) Imbalance
HourCounters Average Yaw Avg. [h] is highly imbalanced (55.1%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.3%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (97.2%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (65.0%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (97.1%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (67.5%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (84.7%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (72.7%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (78.9%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (65.7%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (62.8%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (54.9%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.9%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-14 17:21:12.046725
Analysis finished2025-05-14 17:21:38.080656
Duration26.03 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-14T19:21:38.121171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T19:21:38.203344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24002 
1
 
2206

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Length

2025-05-14T19:21:38.276659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.313102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24002
91.6%
1 2206
 
8.4%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23490 
1
2718 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Length

2025-05-14T19:21:38.358737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.394906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Most occurring characters

ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23490
89.6%
1 2718
 
10.4%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23599 
1
2609 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Length

2025-05-14T19:21:38.439097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.476602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23599
90.0%
1 2609
 
10.0%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23703 
1
2505 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Length

2025-05-14T19:21:38.520591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.556789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23703
90.4%
1 2505
 
9.6%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25295 
1
 
913

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Length

2025-05-14T19:21:38.602429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.637938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25295
96.5%
1 913
 
3.5%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25034 
1
 
1174

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Length

2025-05-14T19:21:38.679889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.717088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25034
95.5%
1 1174
 
4.5%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24985 
1
 
1223

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Length

2025-05-14T19:21:38.759219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.794905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24985
95.3%
1 1223
 
4.7%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25210 
1
 
998

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%

Length

2025-05-14T19:21:38.838684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.874005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25210
96.2%
1 998
 
3.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23099 
1
3109 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%

Length

2025-05-14T19:21:38.916812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:38.955578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23099
88.1%
1 3109
 
11.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25064 
1
 
1144

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%

Length

2025-05-14T19:21:38.999677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.035481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25064
95.6%
1 1144
 
4.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21937 
1
4271 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Length

2025-05-14T19:21:39.079480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.115764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Most occurring characters

ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21937
83.7%
1 4271
 
16.3%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25750 
1
 
458

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Length

2025-05-14T19:21:39.159859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.197416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Most occurring characters

ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25750
98.3%
1 458
 
1.7%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:39.239697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.273107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:39.466399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.499622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23998 
1
 
2210

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%

Length

2025-05-14T19:21:39.538485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.575681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23998
91.6%
1 2210
 
8.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24618 
1
 
1590

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Length

2025-05-14T19:21:39.619949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.655147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring characters

ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24618
93.9%
1 1590
 
6.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:39.699830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.733020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24979 
1
 
1229

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Length

2025-05-14T19:21:39.771968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.808872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24979
95.3%
1 1229
 
4.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24492 
1
 
1716

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Length

2025-05-14T19:21:39.851004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.886250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24492
93.5%
1 1716
 
6.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24515 
1
 
1693

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%

Length

2025-05-14T19:21:39.930120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:39.966010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24515
93.5%
1 1693
 
6.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24305 
1
 
1903

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%

Length

2025-05-14T19:21:40.008265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.045065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24305
92.7%
1 1903
 
7.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24229 
1
 
1979

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Length

2025-05-14T19:21:40.087056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.123987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24229
92.4%
1 1979
 
7.6%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23650 
1
2558 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Length

2025-05-14T19:21:40.165979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.202106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Most occurring characters

ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23650
90.2%
1 2558
 
9.8%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23401 
1
2807 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Length

2025-05-14T19:21:40.247705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.284055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Most occurring characters

ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23401
89.3%
1 2807
 
10.7%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22812 
1
3396 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Length

2025-05-14T19:21:40.327807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.365661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Most occurring characters

ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22812
87.0%
1 3396
 
13.0%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23851 
1
 
2357

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Length

2025-05-14T19:21:40.410048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.446131image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23851
91.0%
1 2357
 
9.0%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22873 
1
3335 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Length

2025-05-14T19:21:40.491778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.528145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Most occurring characters

ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22873
87.3%
1 3335
 
12.7%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25876 
1
 
332

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Length

2025-05-14T19:21:40.572464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.609786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25876
98.7%
1 332
 
1.3%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25711 
1
 
497

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Length

2025-05-14T19:21:40.652099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.688222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25711
98.1%
1 497
 
1.9%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25909 
1
 
299

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Length

2025-05-14T19:21:40.732122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.767700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25909
98.9%
1 299
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24765 
1
 
1443

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Length

2025-05-14T19:21:40.810813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.847893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24765
94.5%
1 1443
 
5.5%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25364 
1
 
844

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Length

2025-05-14T19:21:40.890067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:40.925926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25364
96.8%
1 844
 
3.2%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25583 
1
 
625

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%

Length

2025-05-14T19:21:40.970603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.006502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25583
97.6%
1 625
 
2.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22773 
1
3435 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%

Length

2025-05-14T19:21:41.049492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.087211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%

Most occurring characters

ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22773
86.9%
1 3435
 
13.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:41.131506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.164560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24801 
1
 
1407

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%

Length

2025-05-14T19:21:41.205019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.240283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%

Most occurring characters

ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24801
94.6%
1 1407
 
5.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24049 
1
 
2159

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%

Length

2025-05-14T19:21:41.282447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.320641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24049
91.8%
1 2159
 
8.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23757 
1
2451 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%

Length

2025-05-14T19:21:41.364644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.401153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23757
90.6%
1 2451
 
9.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23752 
1
2456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Length

2025-05-14T19:21:41.446945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.482980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23752
90.6%
1 2456
 
9.4%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25328 
1
 
880

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Length

2025-05-14T19:21:41.526923image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.564025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25328
96.6%
1 880
 
3.4%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24626 
1
 
1582

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%

Length

2025-05-14T19:21:41.606126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.641691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%

Most occurring characters

ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24626
94.0%
1 1582
 
6.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26089 
1
 
119

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Length

2025-05-14T19:21:41.685347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.720799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25959 
1
 
249

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Length

2025-05-14T19:21:41.762712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.799952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25940 
1
 
268

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Length

2025-05-14T19:21:41.841933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.877444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25940
99.0%
1 268
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25947 
1
 
261

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Length

2025-05-14T19:21:41.921235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:41.957354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25947
99.0%
1 261
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25097 
1
 
1111

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Length

2025-05-14T19:21:41.999382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.036529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25097
95.8%
1 1111
 
4.2%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25020 
1
 
1188

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Length

2025-05-14T19:21:42.078661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.114105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25020
95.5%
1 1188
 
4.5%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25059 
1
 
1149

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Length

2025-05-14T19:21:42.157782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.193091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25059
95.6%
1 1149
 
4.4%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24994 
1
 
1214

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Length

2025-05-14T19:21:42.235142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.408506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24994
95.4%
1 1214
 
4.6%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24956 
1
 
1252

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Length

2025-05-14T19:21:42.451101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.486275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24956
95.2%
1 1252
 
4.8%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24343 
1
 
1865

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Length

2025-05-14T19:21:42.529294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.564704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25046 
1
 
1162

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Length

2025-05-14T19:21:42.607476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.644378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25046
95.6%
1 1162
 
4.4%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23925 
1
 
2283

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Length

2025-05-14T19:21:42.686669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.723145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23925
91.3%
1 2283
 
8.7%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22562 
1
3646 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%

Length

2025-05-14T19:21:42.768486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.804848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%

Most occurring characters

ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22562
86.1%
1 3646
 
13.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22647 
1
3561 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Length

2025-05-14T19:21:42.848523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.885980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Most occurring characters

ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22647
86.4%
1 3561
 
13.6%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22239 
1
3969 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Length

2025-05-14T19:21:42.930175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:42.966528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Most occurring characters

ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22239
84.9%
1 3969
 
15.1%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25404 
1
 
804

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Length

2025-05-14T19:21:43.011825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.047307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25404
96.9%
1 804
 
3.1%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25239 
1
 
969

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Length

2025-05-14T19:21:43.090429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.125730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25239
96.3%
1 969
 
3.7%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25096 
1
 
1112

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Length

2025-05-14T19:21:43.167553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.204257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25096
95.8%
1 1112
 
4.2%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25316 
1
 
892

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%

Length

2025-05-14T19:21:43.246363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.281556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25316
96.6%
1 892
 
3.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.324935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.358008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.396564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.431100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.470301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.503303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.543829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.576897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.616155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.650912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.690653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.724152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.765026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.798315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:43.837729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.872877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26174 
1
 
34

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Length

2025-05-14T19:21:43.911889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:43.948201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26174
99.9%
1 34
 
0.1%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:21:43.993677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.029186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:44.071027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.105947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:21:44.144931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.180568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:21:44.224248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.259711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25878 
1
 
330

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Length

2025-05-14T19:21:44.301688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.338734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25878
98.7%
1 330
 
1.3%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24077 
1
 
2131

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Length

2025-05-14T19:21:44.380671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.416841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Most occurring characters

ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24077
91.9%
1 2131
 
8.1%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25104 
1
 
1104

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Length

2025-05-14T19:21:44.462537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.497949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25104
95.8%
1 1104
 
4.2%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24005 
1
 
2203

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%

Length

2025-05-14T19:21:44.540475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.578519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24005
91.6%
1 2203
 
8.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25483 
1
 
725

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%

Length

2025-05-14T19:21:44.622558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.658223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25483
97.2%
1 725
 
2.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22160 
1
4048 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Length

2025-05-14T19:21:44.702791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.739509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Most occurring characters

ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22160
84.6%
1 4048
 
15.4%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24835 
1
 
1373

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Length

2025-05-14T19:21:44.783420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.820680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24835
94.8%
1 1373
 
5.2%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:44.862947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.896319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23781 
1
2427 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Length

2025-05-14T19:21:44.937257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:44.974420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23781
90.7%
1 2427
 
9.3%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23679 
1
2529 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Length

2025-05-14T19:21:45.018875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.056722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23679
90.4%
1 2529
 
9.6%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23959 
1
 
2249

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Length

2025-05-14T19:21:45.100874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.137144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23959
91.4%
1 2249
 
8.6%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22992 
1
3216 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

Length

2025-05-14T19:21:45.322970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.359150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

Most occurring characters

ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22992
87.7%
1 3216
 
12.3%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25063 
1
 
1145

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Length

2025-05-14T19:21:45.402880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.439742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25063
95.6%
1 1145
 
4.4%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25111 
1
 
1097

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

Length

2025-05-14T19:21:45.481909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.517491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25111
95.8%
1 1097
 
4.2%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25355 
1
 
853

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

Length

2025-05-14T19:21:45.560960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.596724image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25355
96.7%
1 853
 
3.3%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23385 
1
2823 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%

Length

2025-05-14T19:21:45.638838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.676900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%

Most occurring characters

ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23385
89.2%
1 2823
 
10.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:45.722374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.755466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26202 
1
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Length

2025-05-14T19:21:45.796551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.832152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26185 
1
 
23

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

Length

2025-05-14T19:21:45.874336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.911416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26185
99.9%
1 23
 
0.1%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26178 
1
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

Length

2025-05-14T19:21:45.953555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:45.989572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26178
99.9%
1 30
 
0.1%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26128 
1
 
80

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

Length

2025-05-14T19:21:46.034070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.069509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26128
99.7%
1 80
 
0.3%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25434 
1
 
774

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Length

2025-05-14T19:21:46.112916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.148428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24090 
1
 
2118

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

Length

2025-05-14T19:21:46.190310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.228527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

Most occurring characters

ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24090
91.9%
1 2118
 
8.1%

HourCounters Average Yaw Avg. [h]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23749 
1
2459 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

Length

2025-05-14T19:21:46.272792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.308904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23749
90.6%
1 2459
 
9.4%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26193 
1
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Length

2025-05-14T19:21:46.355136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.390715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26135 
1
 
73

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Length

2025-05-14T19:21:46.432563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.469732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26135
99.7%
1 73
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24487 
1
 
1721

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

Length

2025-05-14T19:21:46.512192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.547695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24487
93.4%
1 1721
 
6.6%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26131 
1
 
77

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Length

2025-05-14T19:21:46.591640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.627251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26131
99.7%
1 77
 
0.3%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:46.669216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.704239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:46.743181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.776476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:46.817316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.850723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:46.890032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.924870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:46.963965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:46.997913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.038617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.071895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.110748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.145435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.184379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.217492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.258179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.291486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.330492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.365272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:47.404402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.437514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24653 
1
 
1555

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Length

2025-05-14T19:21:47.478455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.514174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Most occurring characters

ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24653
94.1%
1 1555
 
5.9%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25627 
1
 
581

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%

Length

2025-05-14T19:21:47.556302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.593456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25627
97.8%
1 581
 
2.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24980 
1
 
1228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Length

2025-05-14T19:21:47.635540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.671105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24980
95.3%
1 1228
 
4.7%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25334 
1
 
874

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Length

2025-05-14T19:21:47.715123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.750612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25334
96.7%
1 874
 
3.3%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24531 
1
 
1677

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Length

2025-05-14T19:21:47.792790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.829940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24531
93.6%
1 1677
 
6.4%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24333 
1
 
1875

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Length

2025-05-14T19:21:47.872198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.908021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24333
92.8%
1 1875
 
7.2%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23732 
1
2476 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%

Length

2025-05-14T19:21:47.951661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:47.988238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23732
90.6%
1 2476
 
9.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22761 
1
3447 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%

Length

2025-05-14T19:21:48.032538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.070543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%

Most occurring characters

ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22761
86.8%
1 3447
 
13.2%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.115021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.148174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.190064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.369440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:21:48.408181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.444863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Total Active power [W]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.486508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.519817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.560268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.593959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.633142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.667912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.707669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.740715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:21:48.781467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:21:48.814718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Correlations

2025-05-14T19:21:48.933103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Active power limit [W]0.0001.0000.0600.0000.0000.0000.0000.0190.0000.0000.0160.0050.0000.0260.0190.0000.0090.0220.0010.0000.0040.0000.0000.0000.0050.0000.0000.0000.0080.0100.0140.0130.0110.0000.0000.0000.0180.0000.0050.0000.0140.0150.0140.0200.0000.0270.0290.0090.0370.0120.0190.0000.0200.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1060.0480.0070.0030.0160.1040.0840.0200.0450.0070.0000.0000.0100.0600.0600.0020.0110.0000.0080.0000.0000.0130.0000.0000.0000.0000.0120.000
Active power limit source0.0000.0601.0000.0150.0110.0090.0190.0570.0130.0040.0000.0000.0000.0000.0180.0070.0000.0100.0000.0000.0020.0020.0060.0000.0000.0000.0030.0340.0060.0000.0060.0060.0070.0000.0000.0000.0000.0000.0000.0040.0000.0070.0060.0060.0310.0090.0080.0000.0080.0000.0060.0060.0000.0000.0140.0000.0000.0210.0200.0200.0000.0190.0000.0000.0060.0070.0090.1200.0410.0000.0000.0730.4330.0000.0910.0000.0230.0000.0140.0000.7500.7500.0030.0000.0000.0020.0000.0000.0090.0000.0000.0000.0000.0000.005
Ambient Temp. Avg. [°C]0.0000.0000.0151.0000.0000.0130.0200.0160.0000.0040.0150.0100.0100.0080.0000.0090.0450.0060.0210.0180.0000.0140.0000.0090.0140.0030.0010.0280.0300.0280.0090.0000.0180.0050.0130.0080.0070.0500.0000.0160.0140.0100.0080.0120.0000.0190.0110.0090.0080.0150.0060.0000.0100.0230.0160.0060.0130.0000.0000.0000.0160.0080.0080.0680.0200.0400.0370.0230.0180.0160.0270.0000.0190.0170.0000.0000.0270.0000.0070.1120.0150.0150.0260.0160.0170.0220.0000.0160.0170.0150.0030.0040.0110.0000.060
Ambient WindDir Absolute Avg. [°]0.0000.0000.0110.0001.0000.1360.0000.0340.0000.0170.0420.0310.0280.0260.0000.0140.0000.0000.0090.0000.0020.0130.0100.0000.0100.0060.0380.0000.0000.0000.0050.0040.0030.0280.0500.0320.0360.0000.0130.0110.0420.0010.0150.0150.0000.0100.0170.0060.0000.0070.0200.0160.0000.0430.0120.0330.0310.0000.0000.0000.0000.0050.0000.0110.0010.0230.0040.0000.0060.0100.0400.0050.0000.0000.0000.0000.0090.0040.0020.0120.0110.0110.0510.0000.0120.0520.0220.0220.0050.0250.0280.0420.0240.0290.000
Ambient WindDir Relative Avg. [°]0.0000.0000.0090.0130.1361.0000.0000.0280.0000.0020.1060.1470.0600.0520.0000.0370.0210.0000.0000.0120.0000.0350.0140.0210.0400.0000.0920.0000.0000.0000.0060.0130.0180.1030.1520.0720.0830.0030.0130.0090.0820.0140.0110.0130.0000.0090.0040.0030.0000.0110.0020.0060.0000.0830.0210.0870.0390.0000.0000.0000.0210.0140.0250.0330.0000.0150.0060.0440.0410.0000.0780.0000.0000.0380.0000.0000.0100.0070.0030.0120.0090.0090.1030.0000.0000.1140.0170.0380.0130.0570.1040.1270.0560.0710.032
Ambient WindSpeed Avg. [m/s]0.0000.0000.0190.0200.0000.0001.0000.1630.0810.0180.1230.0330.0810.0450.0000.0000.0150.0000.0000.0170.0780.0640.0720.0570.0340.0600.0030.0050.0100.0000.0220.0070.0220.1240.0770.0570.0800.0180.0000.0480.0320.2170.2120.2150.0100.2670.1030.0760.0700.2480.0920.0690.0660.0470.0290.0360.0340.0000.0000.0000.0450.0320.0360.0060.0050.0000.0000.0000.0000.0260.0530.0000.0080.0000.0000.0000.0370.0190.0000.0000.0190.0190.0430.1290.1080.0470.0090.0100.2470.0430.1270.0650.0550.0520.013
Ambient WindSpeed Max. [m/s]0.0000.0190.0570.0160.0340.0280.1631.0000.0270.0550.0660.0580.0460.0290.0000.0000.0000.0210.0070.0030.0410.0330.0380.0400.0210.0360.0000.0130.0000.0000.0280.0150.0160.0710.0800.0360.0500.0100.0000.0130.0330.1070.1090.1080.0000.1150.1450.0390.0900.1140.1220.0410.0720.0380.0150.0290.0180.0000.0000.0000.0080.0170.0250.0000.0000.0050.0000.0000.0000.0250.0420.0000.0320.0000.0000.0000.0500.0170.0000.0080.0570.0570.0340.0510.0560.0330.0000.0060.1170.0210.0700.0660.0370.0320.016
Ambient WindSpeed Min. [m/s]0.0130.0000.0130.0000.0000.0000.0810.0271.0000.0300.0940.0180.1230.0780.0000.0090.0000.0020.0000.0180.0250.0240.0100.0290.0210.0180.0000.0090.0100.0000.0120.0120.0070.0640.0460.1070.0580.0110.0040.0300.0450.0660.0620.0640.0000.0600.0350.1060.0510.0570.0350.1020.0460.0810.0830.0710.0690.0150.0000.0080.0170.0280.0150.0080.0000.0000.0000.0000.0000.0590.0660.0000.0040.0000.0000.0000.0480.0130.0000.0060.0130.0130.0410.0360.0610.0380.0270.0560.0590.0670.0670.0390.0860.0360.000
Ambient WindSpeed StdDev [m/s]0.0000.0000.0040.0040.0170.0020.0180.0550.0301.0000.0420.0000.0290.0740.0000.0000.0000.0050.0000.0080.0110.0000.0210.0040.0000.0060.0050.0060.0000.0050.0240.0220.0220.0190.0370.0000.0700.0030.0080.0000.0150.0240.0300.0360.0000.0360.0400.0440.1310.0250.0420.0170.1250.0190.0280.0220.0230.0000.0000.0000.0230.0190.0080.0000.0260.0030.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0160.0380.0140.0140.0040.0040.0130.0010.0200.0120.0010.0190.0280.0010.0100.0220.0070.0570.000
Blades PitchAngle Avg. [°]0.0000.0160.0000.0150.0420.1060.1230.0660.0940.0421.0000.2590.4550.4740.0000.0220.0190.0220.0000.0280.0520.1110.0380.1130.1260.0580.0520.0220.0210.0160.0000.0000.0000.2740.2390.2800.2620.0640.0000.0440.3040.1530.1340.1420.0000.2410.2300.2430.2880.2360.2190.2200.2700.4640.2000.2370.2490.0000.0000.0000.0650.0550.0480.0260.0210.0300.0100.1530.1220.1550.4120.0390.0060.1470.0350.0760.0710.0920.0270.0000.0000.0000.3830.0810.2690.4130.1140.2590.2380.3710.2940.2140.2400.2190.027
Blades PitchAngle Max. [°]0.0000.0050.0000.0100.0310.1470.0330.0580.0180.0000.2591.0000.1370.1010.0000.0190.0160.0100.0000.0040.0290.0410.0030.0620.0560.0270.1050.0000.0150.0040.0000.0060.0000.1150.2930.0830.0690.0200.0120.0070.2380.0900.0720.0800.0000.1620.1850.1260.1910.1450.1600.1040.1480.1890.0480.2050.0760.0080.0120.0000.0000.0020.0030.0310.0090.0170.0190.0860.0820.0250.1930.0080.0050.0840.0000.0280.1550.0380.0000.0200.0000.0000.2560.0140.1110.2730.0440.0800.1470.1400.1210.2550.0850.0720.028
Blades PitchAngle Min. [°]0.0000.0000.0000.0100.0280.0600.0810.0460.1230.0290.4550.1371.0000.5690.0000.0100.0000.0080.0100.0150.0700.0890.0440.0880.1000.0460.0000.0290.0190.0030.0050.0040.0080.2310.1550.3630.2580.0530.0000.0430.3900.1250.1120.1080.0000.1770.1560.1790.1940.1700.1400.1640.1920.6740.4460.2940.4530.0000.0000.0000.0520.0340.0440.0210.0090.0100.0000.1030.0720.2540.5500.0320.0050.0980.0330.0770.0920.0600.0220.0000.0000.0000.4610.1370.2750.4490.1990.4620.1690.5270.2430.1320.2920.2070.016
Blades PitchAngle StdDev [°]0.0000.0260.0000.0080.0260.0520.0450.0290.0780.0740.4740.1010.5691.0000.0070.0130.0000.0180.0070.0090.0190.0620.0150.0540.0760.0170.0330.0230.0060.0020.0000.0100.0040.1990.1500.2800.4340.0460.0100.0280.3060.1150.0910.1010.0000.1930.1810.2840.2390.1710.1520.2580.2380.5130.2870.2400.4590.0000.0000.0000.0470.0370.0350.0260.0170.0320.0130.1030.0980.2040.4290.0450.0000.1020.0320.0470.0580.1290.0310.0000.0000.0000.3540.1180.2610.3590.1650.5060.1680.3950.2100.1300.2150.3520.013
Controller Ground Temp. Avg. [°C]0.0000.0190.0180.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0071.0000.0090.0000.0000.0100.0000.0000.0000.0000.0070.0080.0000.0000.0000.0080.0000.0000.0020.0000.0000.0000.0000.0000.0050.0030.0000.0000.0000.0040.0080.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0010.0100.0040.0040.0120.0000.0000.0000.0000.0070.0010.0000.0000.0040.0000.0130.0320.0000.0000.0000.0170.0020.0000.0020.0180.0180.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.000
Controller Hub Temp. Avg. [°C]0.0000.0000.0070.0090.0140.0370.0000.0000.0090.0000.0220.0190.0100.0130.0091.0000.0440.0000.0000.0000.0120.0000.0000.0180.0000.0080.0270.0000.0000.0070.0060.0110.0020.0140.0390.0160.0270.0030.0000.0120.0170.0320.0250.0170.0000.0210.0150.0180.0150.0220.0310.0190.0340.0220.0130.0200.0300.0000.0000.0000.0000.0000.0090.0140.0000.0150.0130.0430.0370.0760.0530.0080.0000.0410.0000.0230.0000.0180.0000.0250.0070.0070.0180.0250.0480.0200.0070.0060.0230.0130.0150.0240.0090.0240.041
Controller Top Temp. Avg. [°C]0.0000.0090.0000.0450.0000.0210.0150.0000.0000.0000.0190.0160.0000.0000.0000.0441.0000.0000.0500.0000.0120.0070.0000.0200.0090.0110.0000.0080.0180.0100.0000.0040.0000.0100.0310.0110.0130.0000.0310.0140.0260.0190.0260.0210.0000.0240.0000.0270.0130.0330.0000.0160.0160.0220.0080.0110.0040.0000.0000.0000.0380.0040.0300.0680.0740.0630.0710.0230.0160.0130.0270.0050.0070.0190.0000.0160.0280.0110.0050.1240.0000.0000.0270.0130.0230.0260.0000.0170.0310.0090.0110.0180.0210.0130.046
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0220.0100.0060.0000.0000.0000.0210.0020.0050.0220.0100.0080.0180.0000.0000.0001.0000.0000.0270.0150.0160.0080.0120.0050.0230.0050.0400.0220.0230.0310.0360.0370.0070.0000.0000.0100.0230.0000.0180.0000.0000.0000.0000.0000.0080.0070.0000.0140.0070.0000.0020.0000.0160.0000.0050.0000.0000.0000.0000.0260.0340.0320.0060.0350.0110.0330.0000.0000.0170.0090.0000.0000.0040.0000.0000.0060.0000.0000.0030.0100.0100.0000.0100.0260.0000.0110.0040.0130.0150.0150.0000.0020.0200.010
Controller VCP Temp. Avg. [°C]0.0000.0010.0000.0210.0090.0000.0000.0070.0000.0000.0000.0000.0100.0070.0100.0000.0500.0001.0000.0260.0040.0190.0130.0250.0230.0000.0150.0310.0280.0220.0000.0030.0000.0130.0080.0000.0060.0450.0150.0000.0000.0000.0000.0000.0000.0010.0160.0160.0000.0000.0100.0180.0160.0000.0000.0000.0190.0000.0000.0060.0000.0000.0000.0610.0410.0230.0200.0000.0000.0130.0180.0150.0070.0000.0110.0190.0060.0000.0130.0900.0000.0000.0120.0050.0000.0080.0000.0220.0050.0060.0060.0020.0000.0240.041
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0000.0180.0000.0120.0170.0030.0180.0080.0280.0040.0150.0090.0000.0000.0000.0270.0261.0000.0510.0470.0310.0580.0270.0390.0080.0520.0340.2290.0670.0630.0620.0200.0120.0090.0000.0240.0000.0770.0040.0000.0000.0100.0000.0000.0000.0110.0000.0000.0070.0060.0050.0010.0070.0010.0000.0000.0040.0000.1350.1830.1470.0110.0290.0170.0270.0000.0000.0050.0050.0090.0000.0000.0130.0060.0070.0070.0260.0100.0000.0000.0000.0120.0000.0000.0080.0130.0070.0100.0200.0130.0160.0080.008
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0040.0020.0000.0020.0000.0780.0410.0250.0110.0520.0290.0700.0190.0000.0120.0120.0150.0040.0511.0000.2690.2290.2390.1480.2720.0050.0340.0100.0200.0960.0900.1010.1600.0770.0930.0970.0520.0120.0350.0600.0390.0410.0390.0010.0500.0510.0260.0270.0560.0430.0200.0250.0450.0480.0350.0380.0000.0000.0000.0620.0540.0520.0060.0040.0000.0020.0140.0120.0000.0480.0000.0000.0100.0000.0000.0170.0000.0020.0080.0020.0020.0690.0300.0000.0750.0130.0130.0560.0420.1540.0820.1080.0870.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0020.0140.0130.0350.0640.0330.0240.0000.1110.0410.0890.0620.0000.0000.0070.0160.0190.0470.2691.0000.1610.3990.2320.2540.0330.0660.0580.0170.0920.0740.0860.2060.0980.1530.1220.0350.0140.0190.0870.0350.0380.0440.0000.0520.0600.0410.0430.0580.0550.0410.0380.0890.0430.0490.0570.0000.0000.0000.0320.0280.0300.0070.0000.0100.0000.0470.0430.0000.0910.0000.0000.0430.0000.0040.0000.0090.0280.0000.0020.0020.1170.0450.0000.1240.0110.0360.0600.0800.2120.0950.1470.1120.020
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0060.0000.0100.0140.0720.0380.0100.0210.0380.0030.0440.0150.0000.0000.0000.0080.0130.0310.2290.1611.0000.1790.1270.2320.0510.0560.0120.0210.0700.0850.0630.1220.0500.0600.0680.0190.0000.0420.0080.0570.0610.0630.0000.0620.0840.0160.0480.0640.0780.0250.0430.0190.0210.0290.0330.0000.0000.0000.0320.0290.0370.0000.0090.0000.0000.0220.0130.0130.0180.0000.0000.0180.0000.0000.0130.0240.0460.0180.0060.0060.0230.0320.0240.0290.0110.0050.0640.0310.1120.0700.0450.0650.007
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0000.0090.0000.0210.0570.0400.0290.0040.1130.0620.0880.0540.0070.0180.0200.0120.0250.0580.2390.3990.1791.0000.2810.2800.0200.0790.0460.0340.0970.1070.0740.2050.0880.1420.1130.0560.0230.0210.0800.0360.0360.0350.0000.0490.0690.0440.0460.0570.0540.0240.0290.0810.0450.0540.0460.0000.0000.0000.0490.0400.0440.0240.0070.0130.0000.0280.0240.0150.0910.0000.0000.0240.0000.0000.0000.0000.0210.0000.0000.0000.1050.0590.0000.1140.0000.0310.0560.0840.2060.0970.1410.1050.024
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0050.0000.0140.0100.0400.0340.0210.0210.0000.1260.0560.1000.0760.0080.0000.0090.0050.0230.0270.1480.2320.1270.2811.0000.2030.0590.0850.0660.0430.0610.0500.0480.1800.0940.1760.0940.0470.0080.0190.0990.0280.0270.0250.0000.0410.0550.0500.0500.0440.0440.0380.0370.1160.0550.0750.0460.0000.0000.0000.0410.0350.0350.0250.0160.0300.0230.0350.0280.0190.1280.0000.0000.0280.0000.0000.0010.0040.0000.0000.0000.0000.1420.0420.0000.1490.0000.0540.0410.1050.2040.0900.1510.0900.014
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0000.0030.0060.0000.0600.0360.0180.0060.0580.0270.0460.0170.0000.0080.0110.0230.0000.0390.2720.2540.2320.2800.2031.0000.0600.0660.0300.0300.0860.0860.0890.1460.0680.0830.0780.0260.0070.0370.0400.0310.0320.0290.0000.0310.0430.0210.0280.0330.0370.0240.0270.0380.0300.0260.0140.0000.0000.0000.0440.0460.0450.0070.0030.0150.0000.0140.0090.0010.0440.0100.0000.0100.0110.0150.0290.0000.0150.0050.0000.0000.0610.0220.0070.0660.0000.0100.0330.0430.1470.0780.0890.0740.000
Gear Oil TemperatureLevel1 Avg. [°C]0.0030.0000.0030.0010.0380.0920.0030.0000.0000.0050.0520.1050.0000.0330.0000.0270.0000.0050.0150.0080.0050.0330.0510.0200.0590.0601.0000.0030.0000.0150.0000.0000.0080.0420.1230.0110.0620.0070.0000.0000.0400.0240.0320.0290.0080.0280.0350.0450.0260.0360.0430.0560.0300.0210.0400.0460.0300.0000.0000.0000.0050.0000.0190.0170.0140.0090.0000.0490.0420.0140.0200.0210.0100.0450.0160.0260.0390.0270.0310.0000.0030.0030.0390.0060.0140.0490.0130.0210.0370.0150.0510.1170.0000.0880.028
Generator Bearing Temp. Avg. [°C]0.0000.0000.0340.0280.0000.0000.0050.0130.0090.0060.0220.0000.0290.0230.0000.0000.0080.0400.0310.0520.0340.0660.0560.0790.0850.0660.0031.0000.1360.0350.0450.0570.0670.0180.0000.0410.0040.0220.0180.0000.0120.0000.0050.0020.0000.0020.0000.0000.0000.0000.0000.0000.0000.0240.0230.0190.0080.0000.0000.0000.0200.0400.0400.0230.0470.0460.0530.0000.0000.0140.0250.0000.0170.0000.0000.0000.0140.0000.0000.0070.0340.0340.0160.0130.0000.0200.0000.0110.0000.0180.0260.0120.0410.0070.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0080.0060.0300.0000.0000.0100.0000.0100.0000.0210.0150.0190.0060.0080.0000.0180.0220.0280.0340.0100.0580.0120.0460.0660.0300.0000.1361.0000.0460.0390.0400.0550.0000.0000.0270.0040.0250.0220.0000.0000.0220.0140.0160.0000.0120.0050.0180.0000.0120.0060.0110.0000.0120.0000.0020.0080.0000.0000.0000.0070.0200.0140.0270.0630.0620.0820.0000.0000.0210.0100.0000.0000.0000.0000.0000.0120.0110.0000.0410.0060.0060.0000.0130.0100.0000.0050.0000.0100.0100.0000.0000.0260.0110.012
Generator CoolingWater Temp. Avg. [°C]0.0000.0100.0000.0280.0000.0000.0000.0000.0000.0050.0160.0040.0030.0020.0000.0070.0100.0230.0220.2290.0200.0170.0210.0340.0430.0300.0150.0350.0461.0000.0390.0270.0330.0170.0100.0170.0000.0120.0110.0840.0050.0020.0000.0000.0000.0090.0130.0040.0000.0000.0120.0080.0000.0040.0000.0050.0000.0000.0000.0000.1550.1550.1710.0070.0560.0330.0200.0140.0110.0120.0090.0000.0080.0170.0000.0000.0130.0000.0000.0180.0000.0000.0140.0110.0060.0160.0140.0060.0000.0000.0120.0120.0240.0080.000
Generator Phase1 Temp. Avg. [°C]0.0000.0140.0060.0090.0050.0060.0220.0280.0120.0240.0000.0000.0050.0000.0000.0060.0000.0310.0000.0670.0960.0920.0700.0970.0610.0860.0000.0450.0390.0391.0000.3780.4160.0480.0300.0120.0320.0260.0000.0280.0160.0370.0460.0390.0000.0410.0210.0150.0380.0420.0450.0130.0420.0060.0210.0090.0000.0000.0000.0000.0570.0720.0630.0020.0160.0180.0140.0000.0000.0050.0000.0000.0000.0000.0000.0000.0120.0100.0000.0080.0060.0060.0160.0180.0000.0230.0340.0060.0410.0000.0410.0170.0330.0250.018
Generator Phase2 Temp. Avg. [°C]0.0000.0130.0060.0000.0040.0130.0070.0150.0120.0220.0000.0060.0040.0100.0020.0110.0040.0360.0030.0630.0900.0740.0850.1070.0500.0860.0000.0570.0400.0270.3781.0000.2410.0430.0290.0040.0250.0150.0000.0210.0000.0300.0400.0350.0090.0330.0220.0000.0220.0290.0380.0000.0250.0000.0120.0080.0050.0000.0040.0000.0430.0610.0530.0000.0280.0350.0210.0120.0090.0030.0000.0130.0000.0070.0120.0090.0000.0110.0140.0120.0060.0060.0000.0150.0000.0030.0380.0180.0390.0180.0350.0140.0210.0120.019
Generator Phase3 Temp. Avg. [°C]0.0000.0110.0070.0180.0030.0180.0220.0160.0070.0220.0000.0000.0080.0040.0000.0020.0000.0370.0000.0620.1010.0860.0630.0740.0480.0890.0080.0670.0550.0330.4160.2411.0000.0430.0100.0060.0040.0140.0130.0200.0000.0180.0320.0280.0000.0280.0050.0000.0180.0350.0150.0000.0230.0030.0000.0000.0120.0010.0000.0000.0590.0530.0560.0000.0250.0330.0250.0000.0000.0100.0100.0000.0000.0000.0000.0000.0000.0110.0200.0110.0070.0070.0000.0140.0000.0000.0310.0190.0280.0150.0390.0000.0220.0050.029
Generator RPM Avg. [RPM]0.0000.0000.0000.0050.0280.1030.1240.0710.0640.0190.2740.1150.2310.1990.0000.0140.0100.0070.0130.0200.1600.2060.1220.2050.1800.1460.0420.0180.0000.0170.0480.0430.0431.0000.3960.3770.4840.0490.0050.0140.2110.1330.1180.1210.0010.1690.1840.1490.1820.1690.1630.1180.1620.2460.1020.1940.1590.0000.0060.0000.0390.0400.0340.0110.0000.0110.0000.1120.0920.0310.2470.0220.0000.1140.0090.0660.0000.0440.0000.0000.0000.0000.2890.0430.0970.3180.0000.1270.1670.2020.7610.3710.3450.4260.035
Generator RPM Max. [RPM]0.0000.0000.0000.0130.0500.1520.0770.0800.0460.0370.2390.2930.1550.1500.0000.0390.0310.0000.0080.0120.0770.0980.0500.0880.0940.0680.1230.0000.0000.0100.0300.0290.0100.3961.0000.1540.3220.0300.0000.0350.1470.1030.0890.0940.0000.1460.1870.1590.1920.1290.1660.1290.1610.1750.0450.1920.0880.0000.0000.0000.0340.0380.0310.0430.0210.0320.0000.0860.0820.0580.1900.0200.0000.0860.0040.0360.0070.0480.0130.0240.0000.0000.1880.0000.1450.2190.0380.1230.1270.1210.3360.7690.1380.2660.049
Generator RPM Min. [RPM]0.0000.0000.0000.0080.0320.0720.0570.0360.1070.0000.2800.0830.3630.2800.0000.0160.0110.0000.0000.0090.0930.1530.0600.1420.1760.0830.0110.0410.0270.0170.0120.0040.0060.3770.1541.0000.2690.0540.0000.0500.3330.1190.1170.1220.0000.1190.0990.1720.0960.1410.0880.1630.0860.4010.2870.2450.2680.0000.0030.0000.0570.0330.0510.0320.0210.0330.0100.0800.0490.1580.4410.0060.0040.0730.0000.0490.0900.0530.0120.0000.0000.0000.4150.1160.1650.4140.0210.2730.1440.3250.3930.1520.7620.2270.021
Generator RPM StdDev [RPM]0.0000.0180.0000.0070.0360.0830.0800.0500.0580.0700.2620.0690.2580.4340.0000.0270.0130.0100.0060.0000.0970.1220.0680.1130.0940.0780.0620.0040.0040.0000.0320.0250.0040.4840.3220.2691.0000.0310.0000.0110.2230.1170.1010.1080.0000.1760.1830.2600.2170.1520.1710.2320.2200.2240.0790.1470.2870.0000.0000.0000.0080.0220.0000.0310.0060.0230.0050.1010.0950.0000.2280.0400.0000.1030.0270.0480.0040.1280.0120.0040.0000.0000.2570.0100.1340.2830.0090.3020.1470.1630.4520.2810.2390.7140.030
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0000.0500.0000.0030.0180.0100.0110.0030.0640.0200.0530.0460.0050.0030.0000.0230.0450.0240.0520.0350.0190.0560.0470.0260.0070.0220.0250.0120.0260.0150.0140.0490.0300.0540.0311.0000.0260.0000.0430.0140.0200.0120.0000.0350.0220.0260.0240.0300.0100.0150.0190.0570.0300.0310.0260.0000.0030.0000.0220.0250.0090.1100.0110.0220.0290.0000.0000.0150.0590.0000.0000.0000.0000.0000.0150.0060.0000.0530.0000.0000.0590.0230.0160.0640.0100.0290.0250.0580.0540.0310.0540.0290.000
Grid Busbar Temp. Avg. [°C]0.0000.0050.0000.0000.0130.0130.0000.0000.0040.0080.0000.0120.0000.0100.0030.0000.0310.0000.0150.0000.0120.0140.0000.0230.0080.0070.0000.0180.0220.0110.0000.0000.0130.0050.0000.0000.0000.0261.0000.0000.0000.0050.0070.0080.0170.0000.0000.0000.0000.0000.0050.0000.0000.0030.0090.0000.0070.0000.0000.0000.0120.0000.0000.0250.0400.0350.0510.0000.0000.0190.0130.0000.0000.0060.0000.0000.0000.0000.0030.0360.0000.0000.0000.0130.0020.0000.0200.0110.0000.0100.0000.0000.0000.0080.012
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0040.0160.0110.0090.0480.0130.0300.0000.0440.0070.0430.0280.0000.0120.0140.0180.0000.0770.0350.0190.0420.0210.0190.0370.0000.0000.0000.0840.0280.0210.0200.0140.0350.0500.0110.0000.0001.0000.0440.1550.1530.1460.0000.1300.0620.0910.0600.1410.0620.0870.0580.0320.0680.0000.0000.0000.0020.0000.2880.1320.2730.0080.0200.0250.0300.0540.0530.0030.0230.0000.0000.0490.0000.0000.1050.0120.0240.0100.0040.0040.0440.0350.0930.0360.0000.0000.1420.0210.0110.0210.0470.0070.000
Grid Production CosPhi Avg.0.0000.0140.0000.0140.0420.0820.0320.0330.0450.0150.3040.2380.3900.3060.0000.0170.0260.0000.0000.0040.0600.0870.0080.0800.0990.0400.0400.0120.0000.0050.0160.0000.0000.2110.1470.3330.2230.0430.0000.0441.0000.2040.1920.1990.0120.2220.1830.2040.1980.2970.1910.1970.2170.5710.3130.2210.3490.0000.0000.0000.0590.0360.0440.0300.0090.0250.0120.1240.1130.0000.5340.0210.0000.1300.0090.0600.1940.1070.0230.0110.0000.0000.7060.0000.2090.6800.0500.3890.2990.4410.2200.1350.2530.1900.032
Grid Production CurrentPhase1 Avg. [A]0.0000.0150.0070.0100.0010.0140.2170.1070.0660.0240.1530.0900.1250.1150.0000.0320.0190.0000.0000.0000.0390.0350.0570.0360.0280.0310.0240.0000.0220.0020.0370.0300.0180.1330.1030.1190.1170.0140.0050.1550.2041.0000.7580.6810.0030.5480.2600.3060.2420.6270.2910.2930.2850.1720.1280.0870.1130.0070.0000.0060.1130.0440.0910.0280.0000.0000.0000.1200.1160.0460.1250.0220.0000.1200.0030.0400.2240.0910.0000.0090.0070.0070.1820.1840.3600.1910.0000.0870.6170.1300.1380.0820.1010.0990.014
Grid Production CurrentPhase2 Avg. [A]0.0000.0140.0060.0080.0150.0110.2120.1090.0620.0300.1340.0720.1120.0910.0040.0250.0260.0000.0000.0000.0410.0380.0610.0360.0270.0320.0320.0050.0140.0000.0460.0400.0320.1180.0890.1170.1010.0200.0070.1530.1920.7581.0000.6960.0000.5150.2240.2690.2090.6110.2760.2770.2710.1680.1180.0850.1220.0000.0000.0030.1050.0480.0830.0270.0060.0000.0000.1150.1150.0470.1060.0210.0000.1160.0010.0380.2120.0920.0000.0120.0060.0060.1710.1820.3370.1820.0000.0650.5940.1240.1270.0640.0950.0800.023
Grid Production CurrentPhase3 Avg. [A]0.0000.0200.0060.0120.0150.0130.2150.1080.0640.0360.1420.0800.1080.1010.0080.0170.0210.0000.0000.0100.0390.0440.0630.0350.0250.0290.0290.0020.0160.0000.0390.0350.0280.1210.0940.1220.1080.0120.0080.1460.1990.6810.6961.0000.0000.5490.2340.2830.2220.6310.2960.2800.2780.1620.1240.0810.1090.0000.0000.0000.1020.0580.0850.0170.0000.0000.0000.1140.1140.0480.1140.0210.0000.1150.0020.0390.2080.0870.0000.0070.0060.0060.1790.1850.3550.1810.0000.0720.6160.1210.1320.0660.0980.0860.019
Grid Production Frequency Avg. [Hz]0.0000.0000.0310.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0090.0000.0010.0000.0000.0000.0000.0170.0000.0120.0030.0000.0001.0000.0000.0010.0000.0000.0000.0000.0000.0000.0080.0000.0000.0140.0120.0170.0180.0120.0110.0060.0000.0000.0040.0000.0000.0000.0080.0130.0040.0170.0000.0000.0000.0000.0000.0000.0120.0310.0310.0090.0000.0050.0100.0000.0000.0000.0100.0000.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0000.0270.0090.0190.0100.0090.2670.1150.0600.0360.2410.1620.1770.1930.0000.0210.0240.0080.0010.0000.0500.0520.0620.0490.0410.0310.0280.0020.0120.0090.0410.0330.0280.1690.1460.1190.1760.0350.0000.1300.2220.5480.5150.5490.0001.0000.4040.4430.4330.7430.3760.3430.3760.1810.0870.1120.1310.0000.0040.0000.1050.0680.0830.0010.0030.0000.0000.1030.0970.0540.2200.0000.0000.0960.0000.0000.1410.1210.0040.0070.0090.0090.2150.2640.4560.2150.0160.1390.7140.1440.1740.1270.1010.1530.035
Grid Production PossiblePower Max. [W]0.0000.0290.0080.0110.0170.0040.1030.1450.0350.0400.2300.1850.1560.1810.0000.0150.0000.0070.0160.0000.0510.0600.0840.0690.0550.0430.0350.0000.0050.0130.0210.0220.0050.1840.1870.0990.1830.0220.0000.0620.1830.2600.2240.2340.0010.4041.0000.2970.4320.3560.7120.2440.3550.1800.0470.1310.1460.0060.0090.0000.0580.0430.0500.0000.0000.0000.0030.0960.0950.0620.2200.0170.0000.0900.0150.0130.0480.0950.0440.0150.0080.0080.1950.1010.2860.2080.0140.1310.3580.1420.1980.1610.0900.1810.018
Grid Production PossiblePower Min. [W]0.0000.0090.0000.0090.0060.0030.0760.0390.1060.0440.2430.1260.1790.2840.0000.0180.0270.0000.0160.0110.0260.0410.0160.0440.0500.0210.0450.0000.0180.0040.0150.0000.0000.1490.1590.1720.2600.0260.0000.0910.2040.3060.2690.2830.0000.4430.2971.0000.3330.3820.2940.6240.3250.1860.0720.1080.2050.0000.0050.0060.0920.0410.0660.0100.0050.0040.0000.0920.0950.0630.2270.0080.0000.0960.0000.0030.0900.1270.0180.0190.0000.0000.2070.1060.3170.2120.0000.2680.3810.1400.1570.1330.1430.2190.024
Grid Production PossiblePower StdDev [W]0.0000.0370.0080.0080.0000.0000.0700.0900.0510.1310.2880.1910.1940.2390.0000.0150.0130.0140.0000.0000.0270.0430.0480.0460.0500.0280.0260.0000.0000.0000.0380.0220.0180.1820.1920.0960.2170.0240.0000.0600.1980.2420.2090.2220.0000.4330.4320.3331.0000.3550.3760.2680.7410.2150.0760.1430.1530.0060.0160.0000.0760.0630.0600.0120.0000.0000.0000.1120.1000.0670.2430.0000.0000.1060.0000.0140.0680.1150.0000.0040.0080.0080.2160.1010.2990.2420.0450.1400.3520.1710.1800.1710.0810.1830.016
Grid Production Power Avg. [W]0.0000.0120.0000.0150.0070.0110.2480.1140.0570.0250.2360.1450.1700.1710.0000.0220.0330.0070.0000.0000.0560.0580.0640.0570.0440.0330.0360.0000.0120.0000.0420.0290.0350.1690.1290.1410.1520.0300.0000.1410.2970.6270.6110.6310.0000.7430.3560.3820.3551.0000.3850.3760.4050.2460.0930.1320.1520.0000.0000.0000.1240.0800.0970.0170.0110.0000.0000.1330.1250.0620.2120.0000.0000.1300.0060.0270.1400.1310.0000.0000.0000.0000.3080.2630.4580.2680.0110.1250.8970.1950.1820.1080.1210.1360.032
Grid Production Power Max. [W]0.0000.0190.0060.0060.0200.0020.0920.1220.0350.0420.2190.1600.1400.1520.0000.0310.0000.0000.0100.0070.0430.0550.0780.0540.0440.0370.0430.0000.0060.0120.0450.0380.0150.1630.1660.0880.1710.0100.0050.0620.1910.2910.2760.2960.0000.3760.7120.2940.3760.3851.0000.2570.3820.1860.0730.1200.1350.0160.0130.0000.0640.0560.0490.0100.0030.0000.0000.0870.0830.0420.2080.0000.0000.0780.0000.0000.0400.0770.0290.0080.0060.0060.2090.0830.2810.2280.0000.1050.3790.1390.1730.1360.0720.1730.025
Grid Production Power Min. [W]0.0000.0000.0060.0000.0160.0060.0690.0410.1020.0170.2200.1040.1640.2580.0000.0190.0160.0020.0180.0060.0200.0410.0250.0240.0380.0240.0560.0000.0110.0080.0130.0000.0000.1180.1290.1630.2320.0150.0000.0870.1970.2930.2770.2800.0000.3430.2440.6240.2680.3760.2571.0000.3030.1810.1010.1080.1630.0150.0060.0070.0750.0440.0620.0160.0140.0120.0000.0590.0510.0530.1860.0130.0000.0500.0000.0090.0770.1240.0190.0090.0060.0060.1840.0870.3030.1980.0040.2420.3680.1340.1290.1010.1360.1980.013
Grid Production Power StdDev [W]0.0000.0200.0000.0100.0000.0000.0660.0720.0460.1250.2700.1480.1920.2380.0080.0340.0160.0000.0160.0050.0250.0380.0430.0290.0370.0270.0300.0000.0000.0000.0420.0250.0230.1620.1610.0860.2200.0190.0000.0580.2170.2850.2710.2780.0000.3760.3550.3250.7410.4050.3820.3031.0000.2540.0850.1480.2070.0080.0060.0000.0720.0650.0440.0210.0000.0080.0070.1300.1310.0810.2390.0530.0000.1370.0450.0720.0600.1360.0000.0110.0000.0000.2370.1050.3010.2520.0610.1440.3990.1980.1650.1320.0690.1840.023
Grid Production ReactivePower Avg. [W]0.0000.0000.0000.0230.0430.0830.0470.0380.0810.0190.4640.1890.6740.5130.0000.0220.0220.0160.0000.0010.0450.0890.0190.0810.1160.0380.0210.0240.0120.0040.0060.0000.0030.2460.1750.4010.2240.0570.0030.0320.5710.1720.1680.1620.0080.1810.1800.1860.2150.2460.1860.1810.2541.0000.5520.4040.5860.0000.0000.0000.0500.0300.0300.0320.0100.0190.0000.1140.0870.3050.7360.0100.0060.1090.0030.0590.1330.0900.0240.0070.0000.0000.7200.1390.3180.7410.2210.5770.2410.7670.2570.1580.3010.1850.027
Grid Production ReactivePower Max. [W]0.0000.0000.0140.0160.0120.0210.0290.0150.0830.0280.2000.0480.4460.2870.0000.0130.0080.0000.0000.0070.0480.0430.0210.0450.0550.0300.0400.0230.0000.0000.0210.0120.0000.1020.0450.2870.0790.0300.0090.0680.3130.1280.1180.1240.0000.0870.0470.0720.0760.0930.0730.1010.0850.5521.0000.3350.3810.0000.0000.0070.0600.0240.0570.0240.0000.0000.0080.0620.0360.2530.4210.0000.0000.0560.0000.0330.1740.1220.0130.0110.0140.0140.3490.1320.2030.3410.1770.3320.0920.4370.1050.0410.2260.0440.000
Grid Production ReactivePower Min. [W]0.0000.0000.0000.0060.0330.0870.0360.0290.0710.0220.2370.2050.2940.2400.0000.0200.0110.0050.0000.0010.0350.0490.0290.0540.0750.0260.0460.0190.0020.0050.0090.0080.0000.1940.1920.2450.1470.0310.0000.0000.2210.0870.0850.0810.0000.1120.1310.1080.1430.1320.1200.1080.1480.4040.3351.0000.3310.0000.0000.0000.0090.0130.0130.0290.0110.0260.0230.0740.0560.2410.3610.0080.0000.0720.0040.0170.0300.1470.0180.0110.0000.0000.2870.1860.1420.3110.1240.2840.1260.3270.2130.1740.2010.1240.013
Grid Production ReactivePower StdDev [W]0.0000.0030.0000.0130.0310.0390.0340.0180.0690.0230.2490.0760.4530.4590.0010.0300.0040.0000.0190.0000.0380.0570.0330.0460.0460.0140.0300.0080.0080.0000.0000.0050.0120.1590.0880.2680.2870.0260.0070.0000.3490.1130.1220.1090.0140.1310.1460.2050.1530.1520.1350.1630.2070.5860.3810.3311.0000.0000.0060.0000.0060.0000.0100.0190.0050.0140.0040.0760.0690.2770.5010.0170.0000.0760.0130.0310.0530.1570.0120.0120.0000.0000.4150.1770.2250.4120.2040.5650.1420.4850.1440.0840.1830.2580.023
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0210.0000.0000.0000.0000.0000.0150.0000.0000.0080.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0120.0000.0060.0000.0060.0000.0160.0150.0080.0000.0000.0000.0001.0000.6060.5940.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0100.0000.0000.0000.0020.0000.0020.0000.0210.0210.0000.0000.0150.0000.0000.0030.0070.0000.0000.0000.0000.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0200.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0040.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0060.0000.0030.0000.0030.0000.0020.0000.0000.0000.0000.0170.0040.0090.0050.0160.0000.0130.0060.0060.0000.0000.0000.0060.6061.0000.6180.0000.0060.0000.0000.0050.0000.0000.0000.0000.0050.0030.0000.0090.0000.0000.0000.0000.0000.0090.0000.0200.0200.0000.0020.0130.0100.0030.0000.0000.0000.0110.0000.0080.0040.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0200.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0040.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0030.0000.0180.0000.0000.0060.0000.0000.0000.0070.0000.0000.0070.0000.0000.5940.6181.0000.0000.0000.0100.0000.0000.0130.0000.0110.0110.0140.0040.0000.0090.0000.0000.0000.0060.0000.0160.0000.0200.0200.0000.0070.0120.0000.0000.0090.0000.0000.0030.0000.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0000.0160.0000.0210.0450.0080.0170.0230.0650.0000.0520.0470.0120.0000.0380.0260.0000.1350.0620.0320.0320.0490.0410.0440.0050.0200.0070.1550.0570.0430.0590.0390.0340.0570.0080.0220.0120.2880.0590.1130.1050.1020.0120.1050.0580.0920.0760.1240.0640.0750.0720.0500.0600.0090.0060.0000.0000.0001.0000.2890.4280.0000.0240.0250.0290.0410.0400.0000.0480.0000.0000.0370.0000.0000.0650.0230.0160.0050.0000.0000.0680.0220.0720.0610.0150.0260.1210.0320.0320.0280.0600.0000.000
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0190.0080.0050.0140.0320.0170.0280.0190.0550.0020.0340.0370.0000.0000.0040.0340.0000.1830.0540.0280.0290.0400.0350.0460.0000.0400.0200.1550.0720.0610.0530.0400.0380.0330.0220.0250.0000.1320.0360.0440.0480.0580.0110.0680.0430.0410.0630.0800.0560.0440.0650.0300.0240.0130.0000.0000.0060.0000.2891.0000.3760.0050.0240.0000.0200.0270.0210.0000.0280.0000.0050.0210.0000.0000.0060.0110.0100.0010.0190.0190.0430.0140.0330.0360.0000.0000.0810.0260.0310.0350.0390.0240.000
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0000.0000.0080.0000.0250.0360.0250.0150.0080.0480.0030.0440.0350.0000.0090.0300.0320.0000.1470.0520.0300.0370.0440.0350.0450.0190.0400.0140.1710.0630.0530.0560.0340.0310.0510.0000.0090.0000.2730.0440.0910.0830.0850.0060.0830.0500.0660.0600.0970.0490.0620.0440.0300.0570.0130.0100.0000.0000.0100.4280.3761.0000.0000.0390.0290.0250.0320.0310.0000.0320.0000.0000.0280.0000.0000.0610.0300.0150.0150.0000.0000.0490.0230.0490.0410.0160.0140.0950.0180.0290.0280.0570.0000.004
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0000.0680.0110.0330.0060.0000.0080.0000.0260.0310.0210.0260.0000.0140.0680.0060.0610.0110.0060.0070.0000.0240.0250.0070.0170.0230.0270.0070.0020.0000.0000.0110.0430.0320.0310.1100.0250.0080.0300.0280.0270.0170.0000.0010.0000.0100.0120.0170.0100.0160.0210.0320.0240.0290.0190.0000.0000.0000.0000.0050.0001.0000.0440.0640.0540.0040.0000.0110.0350.0000.0000.0000.0000.0000.0000.0000.0020.0960.0000.0000.0330.0000.0120.0420.0000.0230.0130.0250.0190.0240.0370.0190.036
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0060.0200.0010.0000.0050.0000.0000.0260.0210.0090.0090.0170.0000.0000.0740.0350.0410.0290.0040.0000.0090.0070.0160.0030.0140.0470.0630.0560.0160.0280.0250.0000.0210.0210.0060.0110.0400.0200.0090.0000.0060.0000.0000.0030.0000.0050.0000.0110.0030.0140.0000.0100.0000.0110.0050.0000.0050.0000.0240.0240.0390.0441.0000.1690.1520.0040.0050.0200.0210.0070.0000.0000.0020.0000.0000.0000.0000.0970.0060.0060.0080.0110.0070.0160.0070.0120.0040.0000.0000.0020.0250.0000.018
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0070.0400.0230.0150.0000.0050.0000.0030.0300.0170.0100.0320.0070.0150.0630.0110.0230.0170.0000.0100.0000.0130.0300.0150.0090.0460.0620.0330.0180.0350.0330.0110.0320.0330.0230.0220.0350.0250.0250.0000.0000.0000.0040.0000.0000.0040.0000.0000.0000.0120.0080.0190.0000.0260.0140.0000.0000.0130.0250.0000.0290.0640.1691.0000.1870.0000.0000.0290.0340.0000.0000.0000.0000.0000.0140.0090.0000.1210.0070.0070.0200.0290.0000.0190.0000.0210.0000.0030.0190.0170.0370.0200.040
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0090.0370.0040.0060.0000.0000.0000.0000.0100.0190.0000.0130.0010.0130.0710.0330.0200.0270.0020.0000.0000.0000.0230.0000.0000.0530.0820.0200.0140.0210.0250.0000.0000.0100.0050.0290.0510.0300.0120.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0070.0000.0080.0230.0040.0000.0000.0000.0290.0200.0250.0540.1520.1871.0000.0000.0000.0570.0290.0000.0000.0000.0000.0000.0050.0110.0000.0750.0090.0090.0000.0600.0000.0040.0260.0000.0000.0070.0110.0000.0090.0020.034
HourCounters Average AlarmActive Avg. [h]0.0000.1060.1200.0230.0000.0440.0000.0000.0000.0000.1530.0860.1030.1030.0000.0430.0230.0000.0000.0000.0140.0470.0220.0280.0350.0140.0490.0000.0000.0140.0000.0120.0000.1120.0860.0800.1010.0000.0000.0540.1240.1200.1150.1140.0000.1030.0960.0920.1120.1330.0870.0590.1300.1140.0620.0740.0760.0000.0000.0110.0410.0270.0320.0040.0040.0000.0001.0000.7660.1630.0290.2480.1160.9360.2490.4670.0810.0270.0100.0250.1200.1200.1490.1570.0000.1460.0820.0080.1330.0860.1150.0710.0680.0860.036
HourCounters Average AmbientOk Avg. [h]0.0000.0480.0410.0180.0060.0410.0000.0000.0000.0000.1220.0820.0720.0980.0000.0370.0160.0000.0000.0000.0120.0430.0130.0240.0280.0090.0420.0000.0000.0110.0000.0090.0000.0920.0820.0490.0950.0000.0000.0530.1130.1160.1150.1140.0000.0970.0950.0950.1000.1250.0830.0510.1310.0870.0360.0560.0690.0000.0000.0110.0400.0210.0310.0000.0050.0000.0000.7661.0000.1210.0360.5000.2140.8170.3770.3090.0900.0380.0000.0220.0410.0410.1200.1420.0000.1120.0740.0000.1370.0620.0930.0670.0430.0760.028
HourCounters Average Gen1 Avg. [h]0.0000.0070.0000.0160.0100.0000.0260.0250.0590.0000.1550.0250.2540.2040.0040.0760.0130.0170.0130.0050.0000.0000.0130.0150.0190.0010.0140.0140.0210.0120.0050.0030.0100.0310.0580.1580.0000.0150.0190.0030.0000.0460.0470.0480.0080.0540.0620.0630.0670.0620.0420.0530.0810.3050.2530.2410.2770.0070.0050.0140.0000.0000.0000.0110.0200.0290.0570.1630.1211.0000.5080.0000.0000.1600.0000.0700.0000.0050.0000.0140.0000.0000.0110.5850.3840.0080.3650.1810.0650.2860.0370.0400.1280.0140.000
HourCounters Average Gen2 Avg. [h]0.0000.0030.0000.0270.0400.0780.0530.0420.0660.0120.4120.1930.5500.4290.0000.0530.0270.0090.0180.0050.0480.0910.0180.0910.1280.0440.0200.0250.0100.0090.0000.0000.0100.2470.1900.4410.2280.0590.0130.0230.5340.1250.1060.1140.0130.2200.2200.2270.2430.2120.2080.1860.2390.7360.4210.3610.5010.0000.0030.0040.0480.0280.0320.0350.0210.0340.0290.0290.0360.5081.0000.0260.0180.0380.0000.0290.1060.0940.0230.0090.0000.0000.6800.2560.4800.6660.1450.5250.2140.5990.2560.1790.3340.1860.027
HourCounters Average GridOk Avg. [h]0.0000.0160.0730.0000.0050.0000.0000.0000.0000.0000.0390.0080.0320.0450.0130.0080.0050.0000.0150.0090.0000.0000.0000.0000.0000.0100.0210.0000.0000.0000.0000.0130.0000.0220.0200.0060.0400.0000.0000.0000.0210.0220.0210.0210.0040.0000.0170.0080.0000.0000.0000.0130.0530.0100.0000.0080.0170.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.2480.5000.0000.0261.0000.3830.3600.7270.5900.0000.0180.0000.0220.0730.0730.0100.0000.0060.0150.0000.0000.0330.0000.0190.0110.0000.0330.004
HourCounters Average GridOn Avg. [h]0.0000.1040.4330.0190.0000.0000.0080.0320.0040.0000.0060.0050.0050.0000.0320.0000.0070.0000.0070.0000.0000.0000.0000.0000.0000.0000.0100.0170.0000.0080.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0100.0090.0090.0000.0050.0000.0000.0000.0000.0000.1160.2140.0000.0180.3831.0000.1590.0520.2600.0310.0000.0040.0000.4330.4330.0000.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.000
HourCounters Average Run Avg. [h]0.0000.0840.0000.0170.0000.0380.0000.0000.0000.0000.1470.0840.0980.1020.0000.0410.0190.0040.0000.0000.0100.0430.0180.0240.0280.0100.0450.0000.0000.0170.0000.0070.0000.1140.0860.0730.1030.0000.0060.0490.1300.1200.1160.1150.0000.0960.0900.0960.1060.1300.0780.0500.1370.1090.0560.0720.0760.0000.0000.0000.0370.0210.0280.0000.0000.0000.0000.9360.8170.1600.0380.3600.1591.0000.2150.5810.0790.0280.0000.0220.0000.0000.1430.1540.0000.1390.0800.0070.1380.0820.1170.0730.0640.0880.028
HourCounters Average ServiceOn Avg. [h]0.0000.0200.0910.0000.0000.0000.0000.0000.0000.0000.0350.0000.0330.0320.0000.0000.0000.0000.0110.0130.0000.0000.0000.0000.0000.0110.0160.0000.0000.0000.0000.0120.0000.0090.0040.0000.0270.0000.0000.0000.0090.0030.0010.0020.0000.0000.0150.0000.0000.0060.0000.0000.0450.0030.0000.0040.0130.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.2490.3770.0000.0000.7270.0520.2151.0000.4000.0000.0160.0000.0210.0910.0910.0090.0000.0000.0080.0060.0000.0060.0000.0020.0000.0000.0210.000
HourCounters Average TurbineOk Avg. [h]0.0000.0450.0000.0000.0000.0000.0000.0000.0000.0000.0760.0280.0770.0470.0000.0230.0160.0000.0190.0060.0000.0040.0000.0000.0000.0150.0260.0000.0000.0000.0000.0090.0000.0660.0360.0490.0480.0000.0000.0000.0600.0400.0380.0390.0000.0000.0130.0030.0140.0270.0000.0090.0720.0590.0330.0170.0310.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.4670.3090.0700.0290.5900.2600.5810.4001.0000.0000.0080.0160.0120.0000.0000.0600.0290.0000.0720.0180.0000.0470.0450.0660.0300.0420.0420.000
HourCounters Average WindOk Avg. [h]0.0000.0070.0230.0270.0090.0100.0370.0500.0480.0160.0710.1550.0920.0580.0170.0000.0280.0060.0060.0070.0170.0000.0130.0000.0010.0290.0390.0140.0120.0130.0120.0000.0000.0000.0070.0900.0040.0150.0000.1050.1940.2240.2120.2080.0000.1410.0480.0900.0680.1400.0400.0770.0600.1330.1740.0300.0530.0020.0000.0060.0650.0060.0610.0000.0000.0140.0050.0810.0900.0000.1060.0000.0310.0790.0000.0001.0000.0530.0260.0150.0230.0230.1870.0000.1260.1660.0500.0970.1450.0800.0000.0000.0880.0080.016
HourCounters Average Yaw Avg. [h]0.0000.0000.0000.0000.0040.0070.0190.0170.0130.0380.0920.0380.0600.1290.0020.0180.0110.0000.0000.0070.0000.0090.0240.0000.0040.0000.0270.0000.0110.0000.0100.0110.0110.0440.0480.0530.1280.0060.0000.0120.1070.0910.0920.0870.0000.1210.0950.1270.1150.1310.0770.1240.1360.0900.1220.1470.1570.0000.0000.0000.0230.0110.0300.0000.0000.0090.0110.0270.0380.0050.0940.0180.0000.0280.0160.0080.0531.0000.0080.0000.0000.0000.1080.0050.1140.1130.0120.1250.1200.0700.0440.0460.0470.1100.000
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0140.0070.0020.0030.0000.0000.0000.0140.0270.0000.0220.0310.0000.0000.0050.0000.0130.0260.0020.0280.0460.0210.0000.0150.0310.0000.0000.0000.0000.0140.0200.0000.0130.0120.0120.0000.0030.0240.0230.0000.0000.0000.0000.0040.0440.0180.0000.0000.0290.0190.0000.0240.0130.0180.0120.0020.0090.0160.0160.0100.0150.0020.0000.0000.0000.0100.0000.0000.0230.0000.0040.0000.0000.0160.0260.0081.0000.0070.0140.0140.0200.0130.0090.0220.0060.0330.0030.0040.0090.0110.0080.0060.011
Nacelle Temp. Avg. [°C]0.0000.0100.0000.1120.0120.0120.0000.0080.0060.0140.0000.0200.0000.0000.0020.0250.1240.0030.0900.0100.0080.0000.0180.0000.0000.0050.0000.0070.0410.0180.0080.0120.0110.0000.0240.0000.0040.0530.0360.0100.0110.0090.0120.0070.0120.0070.0150.0190.0040.0000.0080.0090.0110.0070.0110.0110.0120.0000.0000.0000.0050.0010.0150.0960.0970.1210.0750.0250.0220.0140.0090.0220.0000.0220.0210.0120.0150.0000.0071.0000.0000.0000.0070.0130.0050.0100.0060.0100.0070.0000.0000.0060.0060.0090.090
Power factor set point0.0000.0600.7500.0150.0110.0090.0190.0570.0130.0040.0000.0000.0000.0000.0180.0070.0000.0100.0000.0000.0020.0020.0060.0000.0000.0000.0030.0340.0060.0000.0060.0060.0070.0000.0000.0000.0000.0000.0000.0040.0000.0070.0060.0060.0310.0090.0080.0000.0080.0000.0060.0060.0000.0000.0140.0000.0000.0210.0200.0200.0000.0190.0000.0000.0060.0070.0090.1200.0410.0000.0000.0730.4330.0000.0910.0000.0230.0000.0140.0001.0000.7500.0030.0000.0000.0020.0000.0000.0090.0000.0000.0000.0000.0000.005
Power factor set point source0.0000.0600.7500.0150.0110.0090.0190.0570.0130.0040.0000.0000.0000.0000.0180.0070.0000.0100.0000.0000.0020.0020.0060.0000.0000.0000.0030.0340.0060.0000.0060.0060.0070.0000.0000.0000.0000.0000.0000.0040.0000.0070.0060.0060.0310.0090.0080.0000.0080.0000.0060.0060.0000.0000.0140.0000.0000.0210.0200.0200.0000.0190.0000.0000.0060.0070.0090.1200.0410.0000.0000.0730.4330.0000.0910.0000.0230.0000.0140.0000.7501.0000.0030.0000.0000.0020.0000.0000.0090.0000.0000.0000.0000.0000.005
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0020.0030.0260.0510.1030.0430.0340.0410.0130.3830.2560.4610.3540.0000.0180.0270.0000.0120.0000.0690.1170.0230.1050.1420.0610.0390.0160.0000.0140.0160.0000.0000.2890.1880.4150.2570.0590.0000.0440.7060.1820.1710.1790.0090.2150.1950.2070.2160.3080.2090.1840.2370.7200.3490.2870.4150.0000.0000.0000.0680.0430.0490.0330.0080.0200.0000.1490.1200.0110.6800.0100.0000.1430.0090.0600.1870.1080.0200.0070.0030.0031.0000.0000.1900.8700.0380.4580.3230.5620.3000.1830.3120.2230.039
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0110.0000.0160.0000.0000.1290.0510.0360.0010.0810.0140.1370.1180.0100.0250.0130.0100.0050.0120.0300.0450.0320.0590.0420.0220.0060.0130.0130.0110.0180.0150.0140.0430.0000.1160.0100.0230.0130.0350.0000.1840.1820.1850.0000.2640.1010.1060.1010.2630.0830.0870.1050.1390.1320.1860.1770.0000.0020.0070.0220.0140.0230.0000.0110.0290.0600.1570.1420.5850.2560.0000.0000.1540.0000.0290.0000.0050.0130.0130.0000.0000.0001.0000.0160.0000.2720.0610.3090.1700.0480.0040.0940.0080.015
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0000.0000.0170.0120.0000.1080.0560.0610.0200.2690.1110.2750.2610.0000.0480.0230.0260.0000.0000.0000.0000.0240.0000.0000.0070.0140.0000.0100.0060.0000.0000.0000.0970.1450.1650.1340.0160.0020.0930.2090.3600.3370.3550.0050.4560.2860.3170.2990.4580.2810.3030.3010.3180.2030.1420.2250.0150.0130.0120.0720.0330.0490.0120.0070.0000.0000.0000.0000.3840.4800.0060.0000.0000.0000.0000.1260.1140.0090.0050.0000.0000.1900.0161.0000.1840.0960.2830.4760.2430.1100.1160.1340.1000.011
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0000.0080.0020.0220.0520.1140.0470.0330.0380.0120.4130.2730.4490.3590.0000.0200.0260.0000.0080.0000.0750.1240.0290.1140.1490.0660.0490.0200.0000.0160.0230.0030.0000.3180.2190.4140.2830.0640.0000.0360.6800.1910.1820.1810.0100.2150.2080.2120.2420.2680.2280.1980.2520.7410.3410.3110.4120.0000.0100.0000.0610.0360.0410.0420.0160.0190.0040.1460.1120.0080.6660.0150.0100.1390.0080.0720.1660.1130.0220.0100.0020.0020.8700.0000.1841.0000.0400.4490.2610.6060.3290.2060.3120.2420.041
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0000.0000.0220.0170.0090.0000.0270.0010.1140.0440.1990.1650.0000.0070.0000.0110.0000.0080.0130.0110.0110.0000.0000.0000.0130.0000.0050.0140.0340.0380.0310.0000.0380.0210.0090.0100.0200.0000.0500.0000.0000.0000.0000.0160.0140.0000.0450.0110.0000.0040.0610.2210.1770.1240.2040.0000.0030.0000.0150.0000.0160.0000.0070.0000.0260.0820.0740.3650.1450.0000.0000.0800.0060.0180.0500.0120.0060.0060.0000.0000.0380.2720.0960.0401.0000.0850.0130.6140.0080.0000.0070.0040.024
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0000.0000.0160.0220.0380.0100.0060.0560.0190.2590.0800.4620.5060.0000.0060.0170.0040.0220.0130.0130.0360.0050.0310.0540.0100.0210.0110.0000.0060.0060.0180.0190.1270.1230.2730.3020.0290.0110.0000.3890.0870.0650.0720.0000.1390.1310.2680.1400.1250.1050.2420.1440.5770.3320.2840.5650.0030.0000.0090.0260.0000.0140.0230.0120.0210.0000.0080.0000.1810.5250.0000.0000.0070.0000.0000.0970.1250.0330.0100.0000.0000.4580.0610.2830.4490.0851.0000.1240.4720.1290.1140.1830.2470.026
Production LatestAverage Total Active Power Avg. [W]0.0000.0130.0090.0170.0050.0130.2470.1170.0590.0280.2380.1470.1690.1680.0000.0230.0310.0130.0050.0070.0560.0600.0640.0560.0410.0330.0370.0000.0100.0000.0410.0390.0280.1670.1270.1440.1470.0250.0000.1420.2990.6170.5940.6160.0000.7140.3580.3810.3520.8970.3790.3680.3990.2410.0920.1260.1420.0070.0000.0000.1210.0810.0950.0130.0040.0000.0000.1330.1370.0650.2140.0330.0000.1380.0060.0470.1450.1200.0030.0070.0090.0090.3230.3090.4760.2610.0130.1241.0000.1920.1820.1060.1230.1280.037
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0000.0150.0250.0570.0430.0210.0670.0010.3710.1400.5270.3950.0000.0130.0090.0150.0060.0100.0420.0800.0310.0840.1050.0430.0150.0180.0100.0000.0000.0180.0150.2020.1210.3250.1630.0580.0100.0210.4410.1300.1240.1210.0100.1440.1420.1400.1710.1950.1390.1340.1980.7670.4370.3270.4850.0000.0000.0000.0320.0260.0180.0250.0000.0030.0070.0860.0620.2860.5990.0000.0000.0820.0000.0450.0800.0700.0040.0000.0000.0000.5620.1700.2430.6060.6140.4720.1921.0000.2040.1350.2420.1410.008
Rotor RPM Avg. [RPM]0.0000.0000.0000.0030.0280.1040.1270.0700.0670.0100.2940.1210.2430.2100.0000.0150.0110.0150.0060.0200.1540.2120.1120.2060.2040.1470.0510.0260.0000.0120.0410.0350.0390.7610.3360.3930.4520.0540.0000.0110.2200.1380.1270.1320.0000.1740.1980.1570.1800.1820.1730.1290.1650.2570.1050.2130.1440.0000.0110.0030.0320.0310.0290.0190.0000.0190.0110.1150.0930.0370.2560.0190.0000.1170.0020.0660.0000.0440.0090.0000.0000.0000.3000.0480.1100.3290.0080.1290.1820.2041.0000.3100.3630.4000.041
Rotor RPM Max. [RPM]0.0000.0000.0000.0040.0420.1270.0650.0660.0390.0220.2140.2550.1320.1300.0000.0240.0180.0000.0020.0130.0820.0950.0700.0970.0900.0780.1170.0120.0000.0120.0170.0140.0000.3710.7690.1520.2810.0310.0000.0210.1350.0820.0640.0660.0000.1270.1610.1330.1710.1080.1360.1010.1320.1580.0410.1740.0840.0000.0000.0000.0280.0350.0280.0240.0020.0170.0000.0710.0670.0400.1790.0110.0000.0730.0000.0300.0000.0460.0110.0060.0000.0000.1830.0040.1160.2060.0000.1140.1060.1350.3101.0000.1300.2320.034
Rotor RPM Min. [RPM]0.0000.0000.0000.0110.0240.0560.0550.0370.0860.0070.2400.0850.2920.2150.0110.0090.0210.0020.0000.0160.1080.1470.0450.1410.1510.0890.0000.0410.0260.0240.0330.0210.0220.3450.1380.7620.2390.0540.0000.0470.2530.1010.0950.0980.0000.1010.0900.1430.0810.1210.0720.1360.0690.3010.2260.2010.1830.0000.0080.0000.0600.0390.0570.0370.0250.0370.0090.0680.0430.1280.3340.0000.0000.0640.0000.0420.0880.0470.0080.0060.0000.0000.3120.0940.1340.3120.0070.1830.1230.2420.3630.1301.0000.1980.009
Rotor RPM StdDev [RPM]0.0000.0120.0000.0000.0290.0710.0520.0320.0360.0570.2190.0720.2070.3520.0000.0240.0130.0200.0240.0080.0870.1120.0650.1050.0900.0740.0880.0070.0110.0080.0250.0120.0050.4260.2660.2270.7140.0290.0080.0070.1900.0990.0800.0860.0000.1530.1810.2190.1830.1360.1730.1980.1840.1850.0440.1240.2580.0000.0040.0000.0000.0240.0000.0190.0000.0200.0020.0860.0760.0140.1860.0330.0000.0880.0210.0420.0080.1100.0060.0090.0000.0000.2230.0080.1000.2420.0040.2470.1280.1410.4000.2320.1981.0000.033
Spinner Temp. Avg. [°C]0.0000.0000.0050.0600.0000.0320.0130.0160.0000.0000.0270.0280.0160.0130.0000.0410.0460.0100.0410.0080.0000.0200.0070.0240.0140.0000.0280.0000.0120.0000.0180.0190.0290.0350.0490.0210.0300.0000.0120.0000.0320.0140.0230.0190.0000.0350.0180.0240.0160.0320.0250.0130.0230.0270.0000.0130.0230.0000.0000.0000.0000.0000.0040.0360.0180.0400.0340.0360.0280.0000.0270.0040.0000.0280.0000.0000.0160.0000.0110.0900.0050.0050.0390.0150.0110.0410.0240.0260.0370.0080.0410.0340.0090.0331.000

Missing values

2025-05-14T19:21:36.783875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T19:21:37.503252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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32020-01-01 00:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
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62020-01-01 01:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
72020-01-01 01:10:0000000000000000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
82020-01-01 01:20:0000100000010000000000001000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
92020-01-01 01:30:0010110000000000000000000100100000000000000000000000000000000000000000000000101000000000000000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
261982020-06-30 22:20:0000001000000000000000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
261992020-06-30 22:30:0000001000000000000000000000000000000100000000000000000100000000000000000000000000000000000000000010000000000000000000000000000000
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